CPNet: Accurate Contour Preservation for Semantic Segmentation by Mitigating the Impact of Pseudo-boundaries
This repository contains the implementation details of our paper "Accurate Contour Preservation for Semantic Segmentation by Mitigating the Impact of Pseudo-boundaries".
- configs/* : config files
- mmseg/evaluation/metrics/boundary_metric.py: the calculation of boundary IoU
- mmseg/models/decode_heads/*, mmseg/models/necks/* , mmseg/models/segmentors/cascade_encoder_decoder_3.py: model files
- mmse/models/losses/*: loss function
- Linux/MacOS/Windows
- Python 3.7+
- CUDA 10.2+
- PyTorch 1.8+
- mmcv 2.0
- mmsegmentation
Noted: The code is based on mmsegmentation v1.1.2. Just follow this guidance get_started to install the environment and copy or update the code files of this repository to the corresponding files, and everything will be ready.